Architect Production-Ready
Qwen & Gemini Project Agents
Generate isolated workspace context, persona rules, and strict output instructions. Test your agent prompts live in your browser with your own free Gemini API key.
1. Never use corporate jargon.
2. Maximum 120 words.
# SYSTEM INSTRUCTIONS: B2B ENTERPRISE OUTREACH BOT
[PROJECT_METADATA] Scope: STRICT_ISOLATED_WORKSPACE
[PRIMARY_ROLE_AND_PERSONA] Elite B2B SDR & Copywriter
[OPERATIONAL_RULES_AND_CONSTRAINTS] Adhere strictly to word limits and CTA clarity.
Architected for Production LLM Projects
Everything you need to craft strict system instructions, set context boundaries, and test live prompts.
1-Click Industry Presets
Instantly populate production-tested prompt architecture for B2B Sales, Code Audits, E-Commerce, Local SEO, and YouTube Repurposing.
Isolated Memory Scope
Establish explicit workspace context boundaries to prevent cross-chat memory contamination in Qwen Studios and Claude Projects.
BYOK Gemini Live Playground
Paste your free Google Gemini API key to evaluate your constructed system prompt in real-time. 100% browser side, zero server logs.
Dual Export (.MD & .JSON)
Export clean Markdown system instructions (`PROJECT_INSTRUCTIONS.md`) or machine-readable JSON configuration files (`project_config.json`).
How to Deploy Instructions in Qwen & Claude
Follow these 4 simple steps to set up high-performing custom project spaces.
Configure Parameters
Open the tool and choose a starter preset or enter your custom project name, AI persona, negative constraints, and output guidelines.
Test Live with BYOK
Paste your free Gemini API key in the Live Test Playground to verify prompt adherence and tweak guidelines before deployment.
Export .MD / .JSON
Click "📋 Copy System Instructions" or download `PROJECT_INSTRUCTIONS.md` directly to your computer.
Paste into Studio
Navigate to Qwen Studio Projects or Claude Projects, create a new Project, and paste the instructions into the System Prompt box.
Understanding Project Memory Isolation in Qwen & Gemini
Why structured system prompts outperform generic chat prompts in LLM agent workflows.
When developing specialized AI agents using modern LLM architectures (such as Qwen 2.5, Gemini 3 Flash, or Claude 3.5 Sonnet), multi-turn chat drift is a common issue. Without explicit workspace parameters, models tend to revert to generic conversational tones, ignore negative constraints, or leak context across unrelated topics.
1. [PROJECT_METADATA] → Defines scope boundaries and target context window strategy.
2. [PRIMARY_ROLE_AND_PERSONA] → Establishes explicit tone, expertise, and authority level.
3. [OPERATIONAL_RULES_AND_CONSTRAINTS] → Enforces strict negative constraints and CAN-SPAM / security rules.
4. [REQUIRED_OUTPUT_STRUCTURE] → Guarantees consistent markdown formatting or JSON output syntax.
By using the Qwen & Gemini Custom Project Architect, developers and content creators can quickly construct robust instructions that enforce memory isolation, preventing token degradation and maintaining high output standard across hundreds of sequential prompts.
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